class_docstr: RCNN head with two Fully Connected layers
  
  Args:
      mlp_dim (int): num of filters for the fc layers
code: def __call__(self, roi_feat):
      fan = roi_feat.shape[1] * roi_feat.shape[2] * roi_feat.shape[3]
  
      fc6 = fluid.layers.fc(
          input=roi_feat,
          size=self.mlp_dim,
          act="relu",
          name="fc6",
          param_attr=ParamAttr(
              name="fc6_w", initializer=Xavier(fan_out=fan)
          ),
          bias_attr=ParamAttr(
              name="fc6_b", learning_rate=2.0, regularizer=L2Decay(0.0)
          ),
      )
      head_feat = fluid.layers.fc(
          input=fc6,
          size=self.mlp_dim,
          act="relu",
          name="fc7",
          param_attr=ParamAttr(name="fc7_w", initializer=Xavier()),
          bias_attr=ParamAttr(
              name="fc7_b", learning_rate=2.0, regularizer=L2Decay(0.0)
          ),
      )
  
      return head_feat
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from collections import OrderedDict
  from paddle import fluid
  from paddle.fluid.param_attr import ParamAttr
  from paddle.fluid.initializer import Normal, Xavier
  from paddle.fluid.regularizer import L2Decay
  from paddle.fluid.initializer import MSRA
label_desc: Use image node_id 2 for calling the TwoFCHead obj's underlying member method code with example usage: obj.__call__(roi_feat) and returns: head_feat